Do documentation pages get cited by AI?

A complete docs or documentation token appeared in the public hostname or path for 113,295 of 8,316,692 cited-page links, or 1.3623%. The links covered 43,240 pages on 7,781 websites.

Existing content-type studies identify help documentation as a cited format but do not publish its prevalence across a full citation corpus. This study supplies that narrow denominator. It does not show that documentation is more or less likely to earn a citation than an unlabeled page.

At least one documentation-labeled page appeared in 60,197 of 860,399 cited answers, or 6.9964%. At least one appeared somewhere in the observed history for 6,694 of 18,449 organic prompts, or 36.2838%.

Link share, answer reach, and prompt reach answer different questions. Documentation touched more than one-third of tracked prompts during repeated answers while remaining a small part of the source mix overall.

ChatGPT Search used 79,736 documentation-labeled links among 2,280,333 cited-page links, or 3.4967%. Google AI Mode used 33,559 of 6,036,359, or 0.5559%. The rate ratio was 6.2896 to 1, and the gap was 2.9407 percentage points.

Keep the engine attached to every documentation audit. This is an observed source-mix difference, not evidence that either engine prefers documentation or that documentation caused a citation.

Paths supplied 57,047 documentation-labeled links without a documentation hostname, or 50.3526% of the total. Documentation hostnames supplied 45,878 without a matching path label, or 40.4943%, and 10,370 carried the label in both places, or 9.1531%.

A hostname-only audit would miss most of the observed set. Preserve the full cited address when reviewing source types, then inspect the page before classifying its purpose.

The 86 prompts containing the complete word docs or documentation recorded 6,471 documentation-labeled links among 31,399 cited-page links, or 20.6089%. Other organic prompts recorded 106,824 of 8,285,293, or 1.2893%. The rate ratio was 15.9843 to 1.

Page format should follow the question. The explicit-documentation group is small and the result is associative, but it shows why a single all-prompt benchmark can obscure the pages useful for technical evaluation.

Software recorded 15,877 documentation-labeled links among 366,600 cited-page links, or 4.3309%. Data and Analytics recorded 3.5844%, Artificial Intelligence 3.0545%, and Information Technology 2.5031%. Consumer Goods recorded 32 of 160,298, or 0.0200%.

Use the industry cut to choose a comparison set. It does not hold prompt wording, publisher type, or engine mix constant and does not show that industry caused the rate.

The ten leading websites supplied 21,909 of 113,295 documentation-labeled links, or 19.3380%. AWS documentation led with 5,644 links, followed by Grafana with 4,056 and Google Cloud documentation with 2,332.

The observed leaders are concentrated enough to audit but do not form a universal publisher ranking. Compare the documentation sources that appear for the same market, prompt, and engine.

The hostname-or-path rule returned 1.3623%. Another 13,288 links carried docs or documentation only in the page title; including them raised the rate to 1.5220%. The final set had zero duplicate answer-page rows, and 96 documentation-labeled links had no title.

The rule misses documentation without a public label and can include pages that discuss documentation inside a matching path. The audit sample confirms both real product and API documentation and a small number of topical articles. This study does not read page contents, test factual support, measure traffic, or estimate causal lift.

Documentation-labeled pages supplied 1.3623% of links overall. On ChatGPT Search the rate was 3.4967%, 6.2896 times the Google AI Mode rate. When prompts explicitly named documentation it was 20.6089%, 15.9843 times the rate on prompts that did not.

Start with technical evaluation, setup, integration, and troubleshooting questions. Keep the exact cited page, prompt, engine, and market together. Check whether the page directly resolves the question before changing it. Rerun the fixed public-address rule next quarter before calling any difference movement.